Can humans perform mental regression on a graph? Accuracy and bias in the perception of scatterplots
| Autor: | Stanislas Dehaene, Lorenzo Ciccione |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Adult
Linguistics and Language Line fitting Extrapolation Experimental and Cognitive Psychology 050105 experimental psychology Judgment 03 medical and health sciences Deming regression 0302 clinical medicine Bias Artificial Intelligence Linear regression Statistics Developmental and Educational Psychology Humans 0501 psychology and cognitive sciences Mathematics 05 social sciences Regression Euclidean distance Neuropsychology and Physiological Psychology Data point Ordinary least squares Linear Models Perception 030217 neurology & neurosurgery |
| Zdroj: | Cognitive Psychology. 128:101406 |
| ISSN: | 0010-0285 |
| DOI: | 10.1016/j.cogpsych.2021.101406 |
| Popis: | Despite the widespread use of graphs, little is known about how fast and how accurately we can extract information from them. Through a series of four behavioral experiments, we characterized human performance in “mental regression”, i.e. the perception of statistical trends from scatterplots. When presented with a noisy scatterplot, even as briefly as 100 ms, human adults could accurately judge if it was increasing or decreasing, fit a regression line, and extrapolate outside the original data range, for both linear and non-linear functions. Performance was highly consistent across those three tasks of trend judgment, line fitting and extrapolation. Participants’ linear trend judgments took into account the slope, the noise, and the number of data points, and were tightly correlated with the t-test classically used to evaluate the significance of a linear regression. However, they overestimated the absolute value of the regression slope. This bias was inconsistent with ordinary least squares (OLS) regression, which minimizes the sum of square deviations, but consistent with the use of Deming regression, which treats the x and y axes symmetrically and minimizes the Euclidean distance to the fitting line. We speculate that this fast but biased perception of scatterplots may be based on a “neuronal recycling” of the human visual capacity to identify the medial axis of a shape. |
| Databáze: | OpenAIRE |
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